Emad Barsoum
Impact in
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- Emotion and Mood Recognition
- Signal Processing top 2%
- Speech and Audio Processing
- Music and Audio Processing
Papers in
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- Multimodal Machine Learning Applications 2
- Video Analysis and Summarization 2
- Video Surveillance and Tracking Methods 1
- Face recognition and analysis 1
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- Topic Modeling 2
- Natural Language Processing Techniques 1
- Co-authors
- Cha Zhang (2 shared papers)Seyedmahdad Mirsamadi (1 shared paper)Cristian Canton Ferrer (1 shared paper)Sarah Adel Bargal (1 shared paper)John D. Owens (1 shared paper)Weitang Liu (1 shared paper)Takashi Isobe (1 shared paper)Xu Jia (1 shared paper)
- Journals
- 34th Structures, Structural Dynamics and Materials Conference (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesCanadaEgypt
In The Last Decade
Emad Barsoum
5 papers receiving 568 citations
Emad Barsoum's Hit Papers
Peers
Comparison fields: 5 of 51
- Experimental and Cognitive Psychology 468
- Signal Processing 352
- Artificial Intelligence 268
- Computer Vision and Pattern Recognition 169
- Cognitive Neuroscience 62
Countries citing papers authored by Emad Barsoum
This map shows the geographic impact of Emad Barsoum's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Emad Barsoum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emad Barsoum more than expected).
Fields of papers citing papers by Emad Barsoum
This network shows the impact of papers produced by Emad Barsoum. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Emad Barsoum. The network helps show where Emad Barsoum may publish in the future.
Co-authors
The 13 scholars most cited alongside Emad Barsoum, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Automatic speech emotion recognition using recurrent neural networks with local attention Hit paper breakdown → | 2017 | 508 |
| 2 | 2016 | 109 | |
| 3 | Object Localization and Motion Transfer learning with Capsules. | 2018 | 2 |
| 4 | 2024 | 1 | |
| 5 | 1993 | 1 | |
| 6 | 2005 | 1 | |
| 7 | 2024 | 0 |
About Emad Barsoum
Emad Barsoum is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Experimental and Cognitive Psychology, Control and Systems Engineering and Mechanics of Materials, having authored 7 papers that have together received 622 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (2 papers), Emotion and Mood Recognition (2 papers), Video Analysis and Summarization (2 papers), Topic Modeling (2 papers), Speech and Audio Processing (1 paper), Natural Language Processing Techniques (1 paper), Video Surveillance and Tracking Methods (1 paper) and Face recognition and analysis (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (468 citations), Signal Processing (352 citations), Artificial Intelligence (268 citations), Computer Vision and Pattern Recognition (169 citations) and Cognitive Neuroscience (62 citations). Emad Barsoum has collaborated with scholars based in United States, Canada and Egypt. Frequent co-authors include Cha Zhang, Seyedmahdad Mirsamadi, Cristian Canton Ferrer, Sarah Adel Bargal, John D. Owens, Weitang Liu, Takashi Isobe, Xu Jia, Lu Tian and Dong Li. Their work appears in journals such as 34th Structures, Structural Dynamics and Materials Conference and arXiv (Cornell University).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.